Can Artificial Intelligence Applications Promote the Synergistic Improvement of Energy Conservation and Carbon Emission Reduction? Evidence from the Mediating Role of Green New-Quality Productive Forces

Whether artificial intelligence applications can help enterprises achieve both energy conservation and emission reduction is a crucial issue in leveraging digital technology for sustainable development. This paper uses data from listed companies from 2012 to 2024 to explore the relationship between AI applications, green new-quality productive forces, energy conservation and emission reduction. The results show that AI applications have both energy conservation and emission reduction effects, and green new-quality productive forces is an important transmission mechanism for artificial intelligence applications to exert their dual environmental effects, but its mediating effects are heterogeneous: green new-quality productive forces only have both energy conservation and emission reduction effects in the eastern region; in capital-intensive enterprises, green new-quality productive forces reduce energy consumption without reducing emissions; in technology-intensive and labor-intensive enterprises, green new-quality productive forces reduce emissions without reducing energy consumption. Further research reveals that value chain upgrading weakens the energy conservation and emission reduction effects of AI applications, while the integration of data and reality and the improvement of green total factor productivity can enhance the carbon reduction effect of such applications. This study provides policy implications for promoting the coordinated development of intelligent and green technologies, enhancing green new-quality productive forces, and promoting sustainable development.